[HN Gopher] a16z: Adventures in Improving AI Economics
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a16z: Adventures in Improving AI Economics
Author : oliver101
Score : 87 points
Date : 2020-08-13 20:58 UTC (2 hours ago)
(HTM) web link (a16z.com)
(TXT) w3m dump (a16z.com)
| tosh wrote:
| this is more related to the previous a16z article on the topic
| but I found "Data as a Service" by Auren Hoffman a great read for
| thinking about businesses that sell access to machine learning
| models
|
| https://www.safegraph.com/blog/data-as-a-service-bible-every...
| oliver101 wrote:
| > This is the crux of the AI business dilemma. If the economics
| are a function of the problem - not the technology per se - how
| can we improve them?
|
| The article focusses on the costs of resources to build a model
| (annotated data + compute) but the economics are also affected by
| the ongoing cost of making a prediction error. False positives
| and false negatives usually have a different cost and each user
| might have their own preferences:
|
| e.g. "show me all the content that's a bit relevant" vs "show me
| just the content that's really relevant".
|
| If you can write out the loss function in $$$ terms not just
| accuracy, then you're closer to either abandoning the problem or
| finding a profitable AI model.
| mensetmanusman wrote:
| Good analogy about discovery of Pharma molecules.
|
| It's really fun to think about the fact that Tesla has more than
| enough data to unlock autonomous vehicles, but all that is
| missing is the correct AI architecture to get it working...
|
| Who will figure out how to code that? Will it be a breakthrough,
| or can sub-optimal architectures eventually reach equilibrium
| with 10x or 100x the amount of time/data processing.
| rokobobo wrote:
| I'm sorry, but is that true, that Tesla has enough data to
| unlock autonomous vehicles? My experience is that until you get
| an ML model to do X, you never know if you have enough data to
| train it to do X. Or is that just your opinion, that they don't
| need more data?
| mdorazio wrote:
| > Tesla has more than enough data to unlock autonomous vehicles
|
| Many people in the automotive industry, myself included,
| disagree with this statement pretty strongly. Driving data
| quantity is not equivalent to quality and they are severely
| lacking in advanced sensor data.
| antipaul wrote:
| Perhaps. It seems it's still an open question whether AI is
| just about memorizing your data, or can it actually make
| reliable decisions during previously unseen scenarios.
|
| Have we already observed, or collected, all that is possible in
| the "driving" world?
| ipsum2 wrote:
| Most self-driving companies use simulations to see how the
| model performs in unseen scenarios.
| zamadatix wrote:
| "Andreessen Horowitz (known as "a16z") is a venture capital firm
| in Silicon Valley, California"
|
| In case anyone was as confused as I was about what a16z means -
| it's just the company not a new abbreviated term related to AI.
| gilgoomesh wrote:
| Yeah, I find this kind of abbreviation annoying. But there's a
| few words that are commonly abbreviated like this:
|
| i18n -> internationalization
|
| l10n -> localization
|
| g11n -> globalization
|
| l12y -> localizability
|
| a11y -> accessibility
|
| It bothers me because my brain does not jump from the
| abbreviation to the underlying word. I really need to stop and
| think about each one. And I get the numbers wrong when writing
| them.
| andrewtbham wrote:
| What AI companies are they invested in?
|
| Labelbox is the only one I know.
|
| https://a16z.com/portfolio/
| quinnhj wrote:
| Tecton is their most recent high profile ML/AI company:
| https://a16z.com/2020/04/28/investing-in-tecton/
| TuringNYC wrote:
| Also for anyone too young to remember the dot com boom, the
| founding partners (Marc Andreessen and Ben Horowitz) are some
| of the legendary techies from that cycle (of Netscape and
| LoudCloud/Opsware fame, way ahead of their time)
| sabalaba wrote:
| There are 16 characters between the A of Andreessen and the Z
| in Horowitz for those that don't get it.
| alextheparrot wrote:
| a16z has a podcast where they explored gross margins a month
| back. The panel called out AI as an example of a software
| business that has a high likelihood of not having standard SaaS
| margins (Most of the panel thought this could be a limitation).
|
| The podcast is nice because I think it holistically explores
| gross margins in a way that you start to understand how it might
| impact AI as a viable primary business model and valuations
| related to companies who that is the case for. Quite
| complementary to the article.
|
| Might be interesting to people who are interested in this
| article:
| https://open.spotify.com/episode/79lJCrHB3nBn1qXCxKA5s7?si=R...
| cinntaile wrote:
| While I haven't listened to this particular one, I just wanted
| to say that their podcasts are usually quite interesting if
| you're interested in new technology/science.
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